DigitalUmuganda/KinyarwandaTTS_female_voice

Model Description

<!-- Provide a longer summary of what this model is. --> This model is an end-to-end deep-learning-based Kinyarwanda Text-to-Speech (TTS). The model was trained using the Coqui's TTS library, and the YourTTS[1] architecture.

Usage

<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> Install the Coqui's TTS library:

pip install TTS

Download the files from this repo, then run:

tts --text "text" --model_path model.pth --config_path config.json --speakers_file_path speakers.pth --speaker_wav conditioning_audio.wav --out_path out.wav

Where the conditioning audio is a wav file(s) to condition a multi-speaker TTS model with a Speaker Encoder, you can give multiple file paths. The d_vectors is computed as their average.

References

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information should go in this section. --> [1] YourTTS paper

[2] Kinyarwanda TTS: Using a multi-speaker dataset to build a Kinyarwanda TTS model